Arroyabe, Marta F. ORCID: https://orcid.org/0000-0003-3223-0268, Arranz, Carlos F.A. ORCID: https://orcid.org/0000-0002-6866-0684, Fernandez De Arroyabe, Ignacio and Fernandez de Arroyabe, Juan Carlos (2024) Analyzing AI adoption in European SMEs: a study of digital capabilities, innovation, and external environment. Technology in Society, 79:102733. ISSN 0160-791X (Print), 1879-3274 (Online) (doi:10.1016/j.techsoc.2024.102733)

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Abstract

This study investigates the effects of digital capabilities, innovation capabilities, and business environmental support on the adoption of Artificial Intelligence (AI) in Small and Medium-sized Enterprises (SMEs). Utilizing dynamic capabilities and resource dependency theories, we provide a comprehensive and integral analysis of the drivers that facilitate AI adoption in SMEs. We conducted an empirical study encompassing 12,108 SMEs, based on survey data of the Flash Eurobarometer database from the European Union. Our analysis employed a combination of classical regression methods and advanced machine learning techniques, including artificial neural networks and tree regression. Our findings highlight the importance of digital capabilities in driving AI adoption, where complementing innovation capabilities exhibit synergistic effects. Contrary to prevailing literature, business environmental support alone demonstrates limited impact, emphasizing its contingent effectiveness within a well-elaborated institutional framework. Furthermore, the synergy between business environmental support and digital and innovation capabilities has a significant impact on AI adoption in SMEs. However, internal capabilities exert a greater influence on AI adoption in SMEs compared to business environmental support. This study contributes to dynamic capabilities theory by elucidating the interplay of digital and innovation capabilities, offering a nuanced understanding of their combined influence on AI adoption. It also enriches resource dependency theory by highlighting the dynamic nature of business environmental support. For practitioners, our results underscore the need for a balanced investment in digital and innovation capabilities. Policymakers should consider these insights when designing support structures for SMEs, emphasizing a comprehensive approach to foster internal capabilities alongside creating an enabling external environment.

Item Type:	Article
Uncontrolled Keywords:	Artificial intelligence, SMEs, digital capabilities, innovation capabilities, business environmental support
Subjects:	H Social Sciences > H Social Sciences (General) Q Science > Q Science (General) Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / School / Research Centre / Research Group:	Greenwich Business School Greenwich Business School > Networks and Urban Systems Centre (NUSC) Greenwich Business School > Networks and Urban Systems Centre (NUSC) > Connected Cities Research Group (CCRG)
Last Modified:	12 Nov 2025 16:32
URI:	https://gala.gre.ac.uk/id/eprint/51575

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